LCA Case Studies

Abstract

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DOI: http://dx.doi.org/10.1065/lca2002.02.073
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1 Background. The U.S. Government has encouraged shifting from
internal combustion engine vehicles (ICEVs) to alternatively fueled
vehicles such as electric vehicles (EVs) for three primary reasons:
reducing oil dependence, reducing greenhouse gas emissions, and
reducing Clean Air Act criteria pollutant emissions. In comparing
these vehicles, there is uncertainty and variability in emission factors
and performance variables, which cause wide variation in
reported outputs.
2 Objectives. A model was developed to demonstrate the use of
Monte Carlo simulation to predict life cycle emissions and energy
consumption differences between the ICEV versus the EV
on a per kilometer (km) traveled basis. Three EV technologies
are considered: lead-acid, nickel-cadmium, and nickel metal
hydride batteries.
3 Methods. Variables were identified to build life cycle inventories
between the EVs and ICEV. Distributions were selected for
each of the variables and input to Monte Carlo Simulation software
called Crystal Ball 2000®.
4 Results and Discussion. All three EV options reduce U.S. oil
dependence by shifting to domestic coal. The life cycle energy
consumption per kilometer (km) driven for the EVs is comparable
to the ICEV; however, there is wide variation in predicted
energy values. The model predicts that all three EV technologies
will likely increase oxides of sulfur and nitrogen as well as
particulate matter emissions on a per km driven basis. The model
shows a high probability that volatile organic compounds and
carbon monoxide emissions are reduced with the use of EVs.
Lead emissions are also predicted to increase for lead-acid battery
EVs. The EV will not reduce greenhouse gas emissions substantially
and may even increase them based on the current U.S.
reliance on coal for electricity generation. The EV may benefit
public health by relocating air pollutants from urban centers,
where traffic is concentrated, to rural areas where electricity
generation and mining generally occur. The use of Monte Carlo
simulation in life cycle analysis is demonstrated to be an effective
tool to provide further insight on the likelihood of emission
outputs and energy consumption.